Subrata Kumar Dutta (65 results)

Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Condition: New. pp. xii + 194.

Condition: New. pp. xii + 194 Acknowledgements.

Condition: New. pp. xii + 194 Index 1st Edition.

Paperback or Softback. Condition: New. Knowledge at a Glance: English and other Important Subjects. Book.

Condition: New. pp. xix + 257 Illus. (Mostly Col.).

Condition: New. pp. xix + 257.

Condition: New. pp. xix + 257.

Condition: New.

Hardcover. Condition: New. Dust Jacket Condition: New. 1st Edition. Contents: Foreword. 1. Introduction. 2. Role and use of ICT in development communication. 3. Major ICT policy initiatives. 4. E-governance in India. 5. ICT programmes initiated by NGOs. 6. An assessment of the ICT initiative in India. 7. Conclusion. Bibliography. Index. Modern information and communications technologies ICTs have many things to offer for the socio-economic development of a nation. ICTs have the potential to increase agriculture production, provide better health services in remote locations and ensure people's access to information and education. Certain traditional barriers in development can be reduced by improving access to information expanding the market base, enhancing employment opportunities and making government services work better. This book has made an attempt to understand the importance of new ICTs in achieving the desired developmental goals. The topics have been dealt within a logical sequence and the concepts explains in a lucid manner.…

Paperback. Condition: Brand New. 510 pages. 6.00x1.14x9.00 inches. In Stock.

Condition: New. In English.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Hardback. Condition: New. Medical images, in various formats, are used by clinicians to identify abnormalities or markers associated with certain conditions, such as cancers, diseases, abnormalities or other adverse health conditions. Deep learning algorithms use vast volumes of data to train the computer to recognise certain features in the images that are associated with the disease or condition that you wish to identify. Whilst analysing the images by eye can take a lot of time, deep learning algorithms have the benefit of reviewing medical images at a faster rate than a human can, which aids the clinician, speeding up diagnoses and freeing up clinicians' time for other duties. Deep Learning in Medical Image Processing and Analysis introduces the fundamentals of deep learning for biomedical image analysis for applications including ophthalmology, cancer detection and heart disease. The book considers the principles of multi-instance feature selection, swarm optimisation, parallel processing models, artificial neural networks, support vector machines, as well as their design and optimisation, in biomedical applications. Topics such as data security, patient confidentiality, effectiveness and reliability will also be discussed. Written by an international team of experts, this edited book covers principles and applications for industry and academic researchers, scientists, engineers, developers, and designers in the fields of machine learning, deep learning, AI, image processing, signal processing, computer science or related fields. It will also be of interest to standards bodies and regulators, and clinicians using deep learning models.…

Condition: As New. Unread book in perfect condition.

Condition: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Condition: New.

Hardback. Condition: New. Medical images, in various formats, are used by clinicians to identify abnormalities or markers associated with certain conditions, such as cancers, diseases, abnormalities or other adverse health conditions. Deep learning algorithms use vast volumes of data to train the computer to recognise certain features in the images that are associated with the disease or condition that you wish to identify. Whilst analysing the images by eye can take a lot of time, deep learning algorithms have the benefit of reviewing medical images at a faster rate than a human can, which aids the clinician, speeding up diagnoses and freeing up clinicians' time for other duties. Deep Learning in Medical Image Processing and Analysis introduces the fundamentals of deep learning for biomedical image analysis for applications including ophthalmology, cancer detection and heart disease. The book considers the principles of multi-instance feature selection, swarm optimisation, parallel processing models, artificial neural networks, support vector machines, as well as their design and optimisation, in biomedical applications. Topics such as data security, patient confidentiality, effectiveness and reliability will also be discussed. Written by an international team of experts, this edited book covers principles and applications for industry and academic researchers, scientists, engineers, developers, and designers in the fields of machine learning, deep learning, AI, image processing, signal processing, computer science or related fields. It will also be of interest to standards bodies and regulators, and clinicians using deep learning models.…

Hardcover. Condition: Brand New. 400 pages. 9.21x6.14x1.02 inches. In Stock.

Condition: New. In English.

Hardback. Condition: New. Medical images, in various formats, are used by clinicians to identify abnormalities or markers associated with certain conditions, such as cancers, diseases, abnormalities or other adverse health conditions. Deep learning algorithms use vast volumes of data to train the computer to recognise certain features in the images that are associated with the disease or condition that you wish to identify. Whilst analysing the images by eye can take a lot of time, deep learning algorithms have the benefit of reviewing medical images at a faster rate than a human can, which aids the clinician, speeding up diagnoses and freeing up clinicians' time for other duties. Deep Learning in Medical Image Processing and Analysis introduces the fundamentals of deep learning for biomedical image analysis for applications including ophthalmology, cancer detection and heart disease. The book considers the principles of multi-instance feature selection, swarm optimisation, parallel processing models, artificial neural networks, support vector machines, as well as their design and optimisation, in biomedical applications. Topics such as data security, patient confidentiality, effectiveness and reliability will also be discussed. Written by an international team of experts, this edited book covers principles and applications for industry and academic researchers, scientists, engineers, developers, and designers in the fields of machine learning, deep learning, AI, image processing, signal processing, computer science or related fields. It will also be of interest to standards bodies and regulators, and clinicians using deep learning models.…

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New. Provides key insights into how AI can be applied to address the specific challenges of diverse global teamsDiscusses how AI developers consider bias, data privacy, and the ethical implantation of AIAddresses challenges and opportun.

Condition: New.

Hardback. Condition: New. Medical images, in various formats, are used by clinicians to identify abnormalities or markers associated with certain conditions, such as cancers, diseases, abnormalities or other adverse health conditions. Deep learning algorithms use vast volumes of data to train the computer to recognise certain features in the images that are associated with the disease or condition that you wish to identify. Whilst analysing the images by eye can take a lot of time, deep learning algorithms have the benefit of reviewing medical images at a faster rate than a human can, which aids the clinician, speeding up diagnoses and freeing up clinicians' time for other duties. Deep Learning in Medical Image Processing and Analysis introduces the fundamentals of deep learning for biomedical image analysis for applications including ophthalmology, cancer detection and heart disease. The book considers the principles of multi-instance feature selection, swarm optimisation, parallel processing models, artificial neural networks, support vector machines, as well as their design and optimisation, in biomedical applications. Topics such as data security, patient confidentiality, effectiveness and reliability will also be discussed. Written by an international team of experts, this edited book covers principles and applications for industry and academic researchers, scientists, engineers, developers, and designers in the fields of machine learning, deep learning, AI, image processing, signal processing, computer science or related fields. It will also be of interest to standards bodies and regulators, and clinicians using deep learning models.…

Hardcover. Condition: new. Hardcover. This volume constitutes selected papers presented at the International Conference on IoT and its Applications 2020. The research papers presented were carefully reviewed and selected from several initial submissions on the topics - the Internet of Things (IoT) and its applications such as smart cities, smart devices, agriculture, transportation and logistics, healthcare, etc. The book contains peer-reviewed chapters written by leading international scholars from around the world. This book will appeal to students, practitioners, industry professionals, and researchers working in the field of IoT and its integration with other technologies to develop comprehensive solutions to real-life problems. This volume constitutes selected papers presented at the International Conference on IoT and its Applications 2020. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …